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Cited by 313

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3D Constrained Local Model for rigid and non-rigid facial tracking

Baltrusaitis, T., Robinson, P., Morency, L.·2012·2012 IEEE Conference on Computer Vision and Pattern Recognition

Abstract

We present 3D Constrained Local Model (CLM-Z) for robust facial feature tracking under varying pose. Our approach integrates both depth and intensity information in a common framework. We show the benefit of our CLM-Z method in both accuracy and convergence rates over regular CLM formulation through experiments on publicly available datasets. Additionally, we demonstrate a way to combine a rigid head pose tracker with CLM-Z that benefits rigid head tracking. We show better performance than the current state-of-the-art approaches in head pose tracking with our extension of the generalised adaptive view-based appearance model (GAVAM).

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Metadata

Authors
Baltrusaitis, T., Robinson, P., & Morency, L.
Venue
2012 IEEE Conference on Computer Vision and Pattern Recognition
Publisher
IEEE
Published
2012-06
Pages
2610-2617
ISSN
1063-6919 (ISSN-L)
OpenAlex
W2151802865
Cited by
313
References
3
FWCI
19.60
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: 3D Constrained Local Model for rigid and non-rigid facial tracking. https://app.cochat.ai/papers/10.1109/cvpr.2012.6247980
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Baltrusaitis, T., Robinson, P., & Morency, L. (2012). 3D Constrained Local Model for rigid and non-rigid facial tracking. 2012 IEEE Conference on Computer Vision and Pattern Recognition. https://doi.org/10.1109/cvpr.2012.6247980

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